Search Results for "estimates"
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Showing 175 open source projects for "estimates"
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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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Infracost VSCode Extension
See cost estimates for Terraform right in your editor
Infracost's VSCode extension shows you cost estimates for Terraform right in your editor! Prevent costly infrastructure changes before they get into production. Compare configs, instance types, regions etc: copy/paste a code block, make changes and compare them. Quick cost estimate: write a code block and get a cost estimate without having to use AWS, Azure or Google cost calculators, or read the long/complicated pricing web pages. -
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SolidInvoice
Simple and elegant invoicing solution
...It helps you manage clients, contacts, day-to-day billing and more so you can always get paid right and on time. SolidInvoice is capable of handling recurring invoices, quotes and estimates, as well as online payments. You can receive payments from a number of different gateways such as Paypal Express, Stripe Checkout, Be2bill and more. It also supports multiple currencies. SolidInvoice has a powerful and flexible RESTful API so you can easily integrate it to any other service. -
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Infracost
Cloud cost estimates for Terraform in pull requests
...Infracost integrates with Open Policy Agent, Sentinel, and Conftest, enabling DevOps teams to set best practices as policies. Infracost automatically creates detailed, shareable cost estimates which can be sent to clients and managers with different scenarios. Infracost supports over 230 Terraform resources across AWS, Azure and Google. Other IaC tools, such as Pulumi, AWS CloudFormation/CDK and Azure ARM/Bicep are on our roadmap. Infracost can also estimate usage-based resources such as AWS S3 or Lambda! Infracost has many CI/CD integrations so you can easily post cost estimates in pull requests. ... -
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ConformalPrediction.jl
Predictive Uncertainty Quantification through Conformal Prediction
...Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use of dedicated calibration data. -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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PEV2
Postgres Explain Visualizer 2
PEV2 is a web-based tool to visualize PostgreSQL execution plans. It takes EXPLAIN or EXPLAIN ANALYZE output and displays it in an interactive, tree-like format that highlights performance metrics, helping users understand query behavior and bottlenecks. PEV2 is a complete rewrite of the original PEV, offering a modern, user-friendly interface for query optimization. -
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Lasso.jl
Lasso/Elastic Net linear and generalized linear models
Lasso.jl is a pure Julia implementation of the glmnet coordinate descent algorithm for fitting linear and generalized linear Lasso and Elastic Net models. -
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MediaPipe
Cross-platform, customizable ML solutions for live and streaming media
MediaPipe offers open-source cross-platform, customizable ML solutions for live and streaming media. Provides segmentation masks for prominent humans in the scene. MediaPipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance-critical for live experiences. ... -
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Causal ML
Uplift modeling and causal inference with machine learning algorithms
...It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data. Essentially, it estimates the causal impact of intervention T on outcome Y for users with observed features X, without strong assumptions on the model form. An important lever to increase ROI in an advertising campaign is to target the ad to the set of customers who will have a favorable response in a given KPI such as engagement or sales. CATE identifies these customers by estimating the effect of the KPI from ad exposure at the individual level from A/B experiments or historical observational data. -
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ShinyItemAnalysis
Test and Item Analysis via Shiny
...All methods include sample R code which is ready to copy and paste into R and run locally. Several toy data sets are ready to use. You can also upload and analyze your own data. ShinyItemAnalysis provides model equations, parameter estimates and their interpretation. -
Dun and Bradstreet Risk Analytics - Supplier IntelligenceRisk, procurement, and compliance teams across the globe are under pressure to deal with geopolitical and business risks. Third-party risk exposure is impacted by rapidly scaling complexity in domestic and cross-border businesses, along with complicated and diverse regulations. It is extremely important for companies to proactively manage their third-party relationships. An AI-powered solution to mitigate and monitor counterparty risks on a continuous basis, this cutting-edge platform is powered by D&B’s Data Cloud with 520M+ Global Business Records and 2B+ yearly updates for third-party risk insights. With high-risk procurement alerts and multibillion match points, D&B Risk Analytics leverages best-in-class risk data to help drive informed decisions. Perform quick and comprehensive screening, using intelligent workflows. Receive ongoing alerts of key business indicators and disruptions.
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Return YouTube Dislike
Chrome extension to return youtube dislikes
...Additionally, the dislike field in the YouTube API was removed on December 13th, 2021, removing any ability to judge the quality of content before watching. With the removal of dislike stats from the YouTube API, our backend switched to using a combination of scraped dislike stats, and estimates extrapolated from extension user data. None existing YouTube ID will return status code 404 "Not Found". Wrong formed YouTube ID will return 400 "Bad Request". -
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FiniteDifferences.jl
High accuracy derivatives, estimated via numerical finite differences
FiniteDifferences.jl estimates derivatives with finite differences. See also the Python package FDM. FiniteDiff.jl and FiniteDifferences.jl are similar libraries: both calculate approximate derivatives numerically. You should definitely use one or the other, rather than the legacy Calculus.jl finite differencing, or reimplementing it yourself. At some point in the future, they might merge, or one might depend on the other. -
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DeepLabCut
Implementation of DeepLabCut
...We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. The package is open source, fast, robust, and can be used to compute 3D pose estimates or for multi-animals. Please see the original paper and the latest work below! This package is collaboratively developed by the Mathis Group & Mathis Lab at EPFL (releases prior to 2.1.9 were developed at Harvard University). The code is freely available and easy to install in a few clicks with Anaconda (and pypi). DeepLabCut is an open-source Python package for animal pose estimation. -
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BenchmarkTools.jl
A benchmarking framework for the Julia language
BenchmarkTools makes performance tracking of Julia code easy by supplying a framework for writing and running groups of benchmarks as well as comparing benchmark results. This package is used to write and run the benchmarks found in BaseBenchmarks.jl. The CI infrastructure for automated performance testing of the Julia language is not in this package but can be found in Nanosoldier.jl. Our story begins with two packages, "Benchmarks" and "BenchmarkTrackers". The Benchmarks package... -
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Sloc Cloc and Code (scc)
Sloc, Cloc and Code: scc is a very fast accurate code counter
Sloc, Cloc and Code: scc is a very fast accurate code counter with complexity calculations and COCOMO estimates written in pure Go. The tool is similar to cloc, sloccount and tokei. For counting the lines of code, blank lines, comment lines, and physical lines of source code in many programming languages. The goal is to be the fastest code counter possible, but also perform COCOMO calculations like sloccount, estimate code complexity similar to cyclomatic complexity calculators, and produce unique lines of code or DRYness metrics. ... -
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hyperfine
A command-line benchmarking tool
A command-line benchmarking tool. Statistical analysis across multiple runs. Support for arbitrary shell commands. Constant feedback about the benchmark progress and current estimates. Warmup runs can be executed before the actual benchmark. Cache-clearing commands can be set up before each timing run. Statistical outlier detection to detect interference from other programs and caching effects. Export results to various formats: CSV, JSON, Markdown, AsciiDoc. Parameterized benchmarks (e.g. vary the number of threads). ... -
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NannyML
Detecting silent model failure. NannyML estimates performance
NannyML is an open-source python library that allows you to estimate post-deployment model performance (without access to targets), detect data drift, and intelligently link data drift alerts back to changes in model performance. Built for data scientists, NannyML has an easy-to-use interface, and interactive visualizations, is completely model-agnostic, and currently supports all tabular classification use cases. NannyML closes the loop with performance monitoring and post deployment data... -
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see
Visualisation toolbox for beautiful and publication-ready figures
see is an R package that serves as the visualization component of the easystats ecosystem, providing plotting utilities to produce publication-ready visualizations of statistical model parameters, diagnostics, predictions, and performance metrics. It works in conjunction with other easystats packages (such as parameters, performance, modelbased, bayestestR, etc.) to convert model outputs or summary objects into visual forms (dot-and-whisker plots, diagnostic plots, residual plots, etc.). It... -
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AWS IoT FleetWise Edge
AWS IoT FleetWise Edge Agent
...Train autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) with camera data collected from a fleet of production vehicles. Improve electric vehicle (EV) battery range estimates with crowdsourced environmental data, such as weather and driving conditions, from nearby vehicles. Collect select data from nearby vehicles and use it to notify drivers of changing road conditions, such as lane closures or construction. Use near real-time data to proactively detect and mitigate fleet-wide quality issues. -
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BACE for gretl
Bayesian Averaging of Classical Estimates
Bayesian Averaging of Classical Estimates package. -
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Drive Health Analyzer - SSD/HDD Monitor
Monitor disk health, predict failures, track SSD/HDD SMART attributes
...Features real-time alerts, detailed health reports, and automatic background monitoring. The intuitive dashboard displays critical parameters like read/write errors, bad sectors, and remaining lifespan estimates helping users make informed decisions. -
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Hard Disk Sentinel
Hard drive monitoring, disk health, and temperature monitoring tool
Hard Disk Sentinel (HDSentinel) is a comprehensive hard drive monitoring software designed to track the health, performance, and temperature of various types of storage devices including hard disks, SSDs, and external drives. It provides real-time monitoring and detailed reports to help prevent data loss by identifying potential hardware issues early. With a user-friendly interface, it displays critical data such as drive health status, temperature levels, and potential errors, allowing... -
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Stake Crash Predictor
Stake Crash Predictor is a toolkit for stake mines predictor & Plinko.
The Stake Crash Predictor is a focused toolkit that combines statistical analysis, optional server fairness seed hash decrypt helpers, and AI-assisted summaries to help you study rounds on Stake.us. This project centers on the stake mines predictor and stake predictor workflows Demo-focused stake crash predictor app — seed-inspection helpers (SHA-512 / SHA-256), AI-assisted summaries, and demo bot templates for stake mines predictor too, Start in demo mode to test safely. Disclaimer:... -
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JRC QSAR Model Database
(Q)SAR Model Reporting Format Inventory
In the regulatory assessment of chemicals (e.g. under REACH), Quantitative Structure Activity Models (QSAR) are playing an increasingly important role in predicting properties for hazard and risk assessment. This implies both a need to be able to identify relevant QSARs and to use them to derive estimates and/or have access to their precalculated estimates. To help meet these needs, the JRC QSAR Model Database is established and freely accessible through http://qsardb.jrc.ec.europa.eu/qmrf The QSAR Model Reporting Format (QMRF) is a harmonised template for summarising and reporting key information on QSAR models, including the results of any validation studies. ... -
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Large Scale Indoor Camera Positioning
Large Scale Indoor Camera Positioning Using Fiducial Markers
...Our innovative approach uses fiducial markers to initially estimate the pairwise relationship between nearby cameras and then uses a full optimization process that incorporates real-world information to refine these estimates. The method is validated through tests on both artificially created and real-world datasets, showing improved performance over existing methods. This project involves two main types of datasets available at: https://sourceforge.net/projects/indoor-camera-positioning-data/. Developed using CPP , CMake and QT Creator . We include a user-friendly GUI Interface. -
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Concorde-EFB
An Electronic Flight Bag for DC Design Concorde for MSFS 2024
The Concorde EFB (v2.0.2) is an Electronic Flight Bag designed for pilots operating the Concorde, particularly with DC Designs in Microsoft Flight Simulator. This add-on facilitates flight planning through features such as, performance, fuel and time calculations. It also includes an airport database, METAR fetching capabilities, and basic runway feasibility cues as a training aid. The tool is intended for convenience and is open-source for community contributions.
